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Multi-scale LG-mod analysis for a more reliable SAR sea surface wind directions retrieval

Articolo
Data di Pubblicazione:
2021
Abstract:
An improved version of the Local-Gradient-Modified (LG-Mod) algorithm for Sea Surface Wind (SSW) directions retrieval by means of Synthetic Aperture Radar (SAR) images is presented. A "local" multi-scale analysis of wind-aligned SAR patterns is introduced to improve the LG-Mod sensitivity to SAR backscattering modulations, occurring locally with various spatial wavelengths. The Marginal Error parameter is redefined, and the adoption of the Directional Accuracy Maximization Criterion (DAMC) allows for the novel Multi-Scale (MS) LG-Mod to automatically select the local processing scale that may be regarded as optimal for pattern enhancement, once a discrete set of scales has been already fixed. Hence, this optimal scale successfully gives evidence to guarantee the best achievable local direction estimation. The assessment of the MS LG-Mod is carried on both simulated SAR images and a Sentinel-1 (S-1) dataset, consisting of 350 Interferometric Wide Swath Ground Range Multi-Look Detected High-Resolution images, which cover the region of the Gulf of Maine. In the latter case, the removal of artifacts and non-wind features from SAR amplitudes is mandatory before directional estimations. In situ wind observations gathered by the National Oceanic and Atmospheric Administration National Data Buoy Center (NOAA NDBC) are exploited for validation. The findings obtained from S-1 data confirm the ones from simulated patterns. The MS LG-Mod analysis performs better than each single-scale one in terms of both percentages of reliable directions and directional Root Mean Square Error (RMSE) values achieved.
Tipologia CRIS:
01.01 Articolo in rivista
Keywords:
Synthetic Aperture Radar; Sentinel-1; Sea Surface Wind; Local Gradient; Directional Statistics; multi-scale patterns analysis
Elenco autori:
Adamo, Maria; Rana, FABIO MICHELE
Autori di Ateneo:
ADAMO MARIA
RANA FABIO MICHELE
Link alla scheda completa:
https://iris.cnr.it/handle/20.500.14243/396328
Pubblicato in:
REMOTE SENSING (BASEL)
Journal
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http://www.scopus.com/record/display.url?eid=2-s2.0-85103879308&origin=inward
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